Tabla de Contenidos: “…Stroking Shapes: Using Stroke to Edge Your Octagon in RedSpiral Shapes: Stroking Open Shapes Using Cap; Font Shapes: Creating Text Shapes Using Fonts; Summary; Chapter 4: The Depth of Digital Illustration: Using Gradients; Inkscape Illustration: Fill Gradients; Radial Fill Gradients: Enhancing Your Heart Shape; Linear Fill Gradients: Enhancing Your Text Object; Inkscape Illustration: Stroke Gradients; Radial Stroke Gradients: Enhancing Your Spiral; Summary; Chapter 5: The Imagery of Digital Illustration: Using Patterns; Inkscape Illustration: Using Fill Patterns…”

Tabla de Contenidos: “…Cover; Copyright; Credits; About the Author; About the Reviewer; www.PacktPub.com; Table of Contents; Preface; Chapter 1: Getting Started with Material Design; Material properties; Setting up a development environment; Installing Android Studio; Configuring the Android SDK; Emulating Android devices; Connecting a real device; The material theme; Applying styles; Customizing the material theme; Summary; Chapter 2: Building a Mobile Layout; Activities and layouts; RelativeLayouts; LinearLayouts; Gravity properties; Inserting and scaling images; Strings and translation; Screen rotation…”

Tabla de Contenidos: “…""Java and JVM Languages""""R""; ""Python""; ""SAS""; ""Notes""; ""Part Two Turning Data into Business Value""; ""Chapter 4 Predictive Modeling""; ""A Methodology for Building Models""; ""sEMMA""; ""Binary Classification""; ""Multilevel Classification""; ""Interval Prediction""; ""Assessment of Predictive Models""; ""Notes""; ""Chapter 5 Common Predictive Modeling Techniques""; ""RFM""; ""Regression""; ""Generalized Linear Models""; ""Neural Networks""; ""Decision and Regression Trees""; ""Support Vector Machines""; ""Bayesian Methods Network Classification""; ""Ensemble Methods""; ""Notes""…”

Tabla de Contenidos: “…Business Process Modeling -- Meronymy-Based Aggregation of Activities in Business Process Models -- Leveraging Business Process Models for ETL Design -- Adaptation in Open Systems: Giving Interaction Its Rightful Place -- Requirements Engineering and Modeling 1 -- Information Use in Solving a Well-Structured IS Problem: The Roles of IS and Application Domain Knowledge -- Finding Solutions in Goal Models: An Interactive Backward Reasoning Approach -- The Model Role Level – A Vision -- Requirements Engineering and Modeling 2 -- Establishing Regulatory Compliance for Information System Requirements: An Experience Report from the Health Care Domain -- Decision-Making Ontology for Information System Engineering -- Reasoning with Optional and Preferred Requirements -- Data Evolution and Adaptation -- A Conceptual Approach to Database Applications Evolution -- Automated Co-evolution of Conceptual Models, Physical Databases, and Mappings -- A SchemaGuide for Accelerating the View Adaptation Process -- Operations on Spatio-temporal Data -- Complexity of Reasoning over Temporal Data Models -- Using Preaggregation to Speed Up Scaling Operations on Massive Spatio-temporal Data -- Situation Prediction Nets -- Model Abstraction, Feature Modeling, and Filtering -- Granularity in Conceptual Modelling: Application to Metamodels -- Feature Assembly: A New Feature Modeling Technique -- A Method for Filtering Large Conceptual Schemas -- Integration and Composition -- Measuring the Quality of an Integrated Schema -- Contextual Factors in Database Integration — A Delphi Study -- Building Dynamic Models of Service Compositions with Simulation of Provision Resources -- Consistency, Satisfiability and Compliance Checking -- Maintaining Consistency of Probabilistic Databases: A Linear Programming Approach -- Full Satisfiability of UML Class Diagrams -- On Enabling Data-Aware Compliance Checking of Business Process Models -- Using Ontologies for Query Answering -- Query Answering under Expressive Entity-Relationship Schemata -- SQOWL: Type Inference in an RDBMS -- Querying Databases with Taxonomies -- Document and Query Processing -- What Is Wrong with Digital Documents? …”

Tabla de Contenidos: “…Co-producing knowledge for action -- Conclusion -- 8 Looking Forward: From Fear to Hope, from Control to Care -- An uncertain world -- Navigating uncertainty -- Complex, non-linear systems -- Individual and collective capacities for generating reliability -- Policy and decision-making processes -- Political economy contexts -- Ways forward? …”

Tabla de Contenidos: “…Machine generated contents note: Chapter 1: Signal generation in radiation detectors 1.1 Detector types 1.2 Signal induction mechanism 1.3 Pulses from ionization detectors 1.4 Scintillation detectors References Chapter 2: Signals, systems, noise and interferences 2.1 Pulse signals definitions 2.2 Operational amplifiers and feedback 2.3 Linear signal processing systems 2.4 Noise and interference 2.5 Signal transmission 2.6 Logic circuits References Chapter 3: Preamplifiers 3.1 Background 3.2 Charge-sensitive preamplifiers 3.3 Current-sensitive preamplifiers 3.4 Voltage-sensitive preamplifiers 3.5 Noise in preamplifier systems 3.6 ASIC preamplifiers 3.7 Preamplifiers for scintillation detectors 3.8 Detector bias supplies References Chapter 4: Energy measurement 4.1 Generals 4.2 Amplitude fluctuations 4.3 Amplifier/Shaper 4.4 Pulse amplitude analysis 4.5 Dead-time 4.6 ASIC pulse processing systems References Chapter 5: Pulse counting and current measurements 5.1 Background 5.2 Pulse counting systems 5.3 Current mode operation 5.4 ASIC systems for radiation intensity measurement 5.5 Campbell's mode operation References Chapter 6: Timing measurements 6.1 Introduction 6.2 Time pick-off techniques 6.3 Time interval measuring devices 6.4 Timing performance of different detectors References Chapter 7: Position sensing 7.1 Position readout concepts 7.2 Individual readout 7.3 Charge division method 7.4 Rise-time method 7.5 Delay-line method References Chapter 8: Pulse-shape discrimination 8.1 Principles of pulse-shape discrimination 8.2 Amplitude-based methods 8.3 Zero-crossing method 8.4 Rise-time measurement method 8.5 Comparison of pulse-shape discrimination methods References Chapter 9: Introduction to digital signals and systems 9.1 Background 9.2 Digital signals 9.3 ADCs 9.4 Digital signal processing References Chapter 10: Digital radiation measurement systems 10.1 Digital systems 10.2 Energy spectroscopy applications 10.3 Pulse timing applications 10.4 Digital pulse-shape discrimination References Index…”

Tabla de Contenidos: “…; ""RequestAnimationFrame""; ""Linear Interpolation""; ""Follow the Mouse""; ""Bouncing Box""…”

Tabla de Contenidos: “…; What do we mean by 'digital'?; The binary code; Linear and logarithmic sampling; Image acquisition; The 16 mm DI route; Deliverables; Part Three The Cinematographer's Craft; 10 Exposure meters; Camera speed; Shutter speed; Average scene reflectance values; Types of exposure meter; 11 Lighting ratios; Defining a lighting ratio; Visualizing lighting ratios; Lighting ratios for film and television; Lighting ratios when shooting for both cinema and television…”

Tabla de Contenidos: “…Summary and Conclusions; References; Appendix: Linear Discriminant Analysis; Claus Weihs and Ursula Garczarek: Stability of Multivariate Representation of Business Cycles over Time; 1. …”

Tabla de Contenidos: “…Daylighting and ventilation in energy efficient factoriesImproving sustainability in healthcare with better space design quality; A linear reciprocating thermomagnetic motor powered by water heated using solar energy; Environmental quickscans as a decision supporting tool: Scanning the embodied energy of different fibre treatments in the development of biocomposite building products; A bottom-up perspective upon climate change-approaches towards the local scale and microclimatic assessment; Energy price differential and industrial production growth in Mexico: A wavelet approach…”

Tabla de Contenidos: “…11 Inside mixers (April 1991)12 Electronic analogue switching, Part I: CMOS gates (January 2004); 13 Electronic analogue switching, Part II: discrete FETs (February 2002); Power Amplifiers; 14 Sound mosfet design (September 1990); 15 FETs versus BJTs: the linearity competition (May 1995); 16 Distortion in power amplifiers, Part I: the sources of distortion (August 1993); 17 Distortion in power amplifiers, Part II: the input stage (September 1993); 18 Distortion in power amplifiers, Part III: the voltage-amplifier stage (October 1993)…”

Tabla de Contenidos: “…9.1 Constraint Systems9.2 Local Propagation Networks; 9.3 Linear Equations; 9.4 linogram: A Drawing System; 9.5 Conclusion; Index; Function Index; A Note About the Cover…”

Tabla de Contenidos: “…Chapter 8: Searching for High-Frequency Trading Opportunities STATISTICAL PROPERTIES OF RETURNS; LINEAR ECONOMETRIC MODELS; VOLATILITY MODELING; NONLINEAR MODELS; CONCLUSION; Chapter 9: Working with Tick Data; PROPERTIES OF TICK DATA; QUANTITY AND QUALITY OF TICK DATA; BID-ASK SPREADS; BID-ASK BOUNCE; MODELING ARRIVALS OF TICK DATA; APPLYING TRADITIONAL ECONOMETRIC TECHNIQUES TO TICK DATA; CONCLUSION; Chapter 10: Trading on Market Microstructure; OVERVIEW OF INVENTORY TRADING STRATEGIES; ORDERS, TRADERS, AND LIQUIDITY; PROFITABLE MARKET MAKING; DIRECTIONAL LIQUIDITY PROVISION; CONCLUSION…”

Tabla de Contenidos: “…Mathematical Preliminaries; 2.1 Linear Operations on Pictures; 2.2 Discrete Picture Transforms; 2.3 Random Variables; 2.4 Random Fields; 2.5 Vector Space Representation of Images; References; Chapter 3. …”

Tabla de Contenidos: “…Regression: Predicting Page Views -- Introducing Regression -- The Baseline Model -- Regression Using Dummy Variables -- Linear Regression in a Nutshell -- Predicting Web Traffic -- Defining Correlation -- 6. …”

Tabla de Contenidos: “…PREFACE TO THE 2011 EDITION xxi -- CHAPTER 1 INTRODUCTION 1 -- PART I HISTORICAL BACKGROUND -- CHAPTER 2 SYNTHETIC A UDIO: A BRIEF HISTORY 9 -- CHAPTER 3 SPEECH ANALYSIS AND SYNTHESIS OVERVIEW 21 -- CHAPTER 4 BRIEF HISTORY OF AUTOMATIC SPEECH RECOGNITION 40 -- CHAPTER 5 SPEECH-RECOGNITION OVERVIEW 59 -- PART II MATHEMATICAL BACKGROUND -- CHAPTER 6 DIGITAL SIGNAL PROCESSING 73 -- CHAPTER 7 DIGITAL FILTERSAND DISCRETE FOURIER TRANSFORM 87 -- CHAPTER 8 PATTERN CLASSIFICATION 105 -- CHAPTER 9 STATISTICAL PATTERN CLASSIFICATION 124 -- PART III ACOUSTICS -- CHAPTER 10 WAVE BASICS 141 -- CHAPTER 11 ACOUSTIC TUBE MODELING OF SPEECH PRODUCTION 152 -- CHAPTER 12 MUSICAL INSTRUMENT ACOUSTICS 158 -- CHAPTER 13 ROOM ACOUSTICS 179 -- PART IV AUDITORY PERCEPTION -- CHAPTER 14 EAR PHYSIOLOGY 193 -- CHAPTER 15 PSYCHOACOUSTICS 209 -- CHAPTER 16 MODELS OF PITCH PERCEPTION 218 -- CHAPTER 17 SPEECH PERCEPTION 232 -- CHAPTER 18 HUMAN SPEECH RECOGNITION 250 -- PART V SPEECH FEATURES -- CHAPTER 19 THE AUDITORY SYSTEM AS A FILTER BANK 263 -- CHAPTER 20 THE CEPSTRUM AS A SPECTRAL ANALYZER 277 -- CHAPTER 21 LINEAR PREDICTION 286 -- PART VI A UTOMATIC SPEECH RECOGNITION -- CHAPTER 22 FEATURE EXTRACTION FOR ASR 301 -- CHAPTER 23 LINGUISTIC CATEGORIES FOR SPEECH RECOGNITION 319 -- CHAPTER 24 DETERMINISTIC SEQUENCE RECOGNITION FOR ASR 337 -- CHAPTER 25 STATISTICAL SEQUENCE RECOGNITION 350 -- CHAPTER 26 STATISTICAL MODEL TRAINING 364 -- CHAPTER 27 DISCRIMINANT ACOUSTIC PROBABILITY ESTIMATION 381 -- CHAPTER 28 ACOUSTIC MODEL TRAINING: FURTHER TOPICS 394 -- CHAPTER 29 SPEECH RECOGNITION AND UNDERSTANDING 416 -- PART VII SYNTHESIS AND CODING -- CHAPTER 30 SPEECH SYNTHESIS 431 -- CHAPTER 31 PITCH DETECTION 455 -- CHAPTER 32 VOCODERS 473 -- CHAPTER 33 LOW-RATE VOCODERS 493 -- CHAPTER 34 MEDIUM-RATE AND HIGH-RATE VOCODERS 505 -- CHAPTER 35 PERCEPTUAL A UDIO CODING 531 -- PART VIII OTHER APPLICATIONS -- CHAPTER 36 SOME ASPECTS OF COMPUTER MUSIC SYNTHESIS 553 -- CHAPTER 37 MUSIC SIGNAL ANALYSIS 567 -- CHAPTER 38 MUSIC RETRIEVAL 581.…”

Tabla de Contenidos: “…Ch 15 Making Lean Six Sigma Work Formal Network vs Informal Network Linear vs Circular Causes / Use SWAT Teams / Risk Free Way to Implement LSS / Can LSS Kill Your Company? …”

Tabla de Contenidos: “…; SYSTEMS DEVELOPMENT AND OTHER DISCIPLINES; OFFSHORING AND OUTSOURCING OF SYSTEMS DEVELOPMENT; IN THE REST OF THIS BOOK; FURTHER READING; 2 LIFECYCLE TYPES AND THEIR RATIONALES; CONTENTS OF THIS CHAPTER; INTRODUCTION TO SYSTEM DEVELOPMENT LIFECYCLES; WHAT WE MEAN BY 'SYSTEM DEVELOPMENT LIFECYCLE'; LIFECYCLES BASED ON THE LINEAR APPROACH; LIFECYCLES BASED ON THE EVOLUTIONARY APPROACH; THE IMPACT OF AGILE…”

Tabla de Contenidos: “…Front Cover; Contents; Chapter 12 - Introduction to Second-Best Analysis; Chapter 13 - The Second-Best Theory of Taxation in One-Consumer Economies with Linear Production Technology; GOVERNMENT EXPENDITURE THEORY: PHILOSOPHICAL UNDERPINNINGS; THE THEORY OF TAXATION; THE THEORY OF PUBLIC CHOICE; BEHAVIORAL PUBLIC FINANCE; SUMMARY; A BASELINE GENERAL EQUILIBRIUM MODEL; FIRST-BEST INSIGHTS; MAXIMIZING SOCIAL WELFARE; REFERENCES; SECOND-BEST ANALYSIS; CONCLUSION; SOCIAL WELFARE AND THE DISTRIBUTION OF INCOME: THE ATKINSON FRAMEWORK; THE CONDENSED MODEL FOR PRODUCTION EXTERNALITIES…”

Tabla de Contenidos: “…-- Subtopic B: Navigating the Platform -- Introducing Jupyter Notebooks -- Subtopic C: Jupyter Features -- Explore some of Jupyter's most useful features -- Converting a Jupyter Notebook to a Python Script -- Subtopic D: Python Libraries -- Import the external libraries and set up the plotting environment -- Our First Analysis - The Boston Housing Dataset -- Subtopic A: Loading the Data into Jupyter Using a Pandas DataFrame -- Load the Boston housing dataset -- Subtopic B: Data Exploration -- Explore the Boston housing dataset -- Subtopic C: Introduction to Predictive Analytics with Jupyter Notebooks -- Linear models with Seaborn and scikit-learn -- Activity B: Building a Third-Order Polynomial Model -- Subtopic D: Using Categorical Features for Segmentation Analysis -- Create categorical fields from continuous variables and make segmented visualizations -- Summary -- Data Cleaning and Advanced Machine Learning -- Preparing to Train a Predictive Model -- Subtopic A: Determining a Plan for Predictive Analytics -- Subtopic B: Preprocessing Data for Machine Learning -- Explore data preprocessing tools and methods -- Activity A: Preparing to Train a Predictive Model for the Employee-Retention Problem -- Training Classification Models -- Subtopic A: Introduction to Classification Algorithms -- Training two-feature classification models with scikit-learn -- The plot_decision_regions Function -- Training k-nearest neighbors for our model -- Training a Random Forest -- Subtopic B: Assessing Models with k-Fold Cross-Validation and Validation Curves -- Using k-fold cross validation and validation curves in Python with scikit-learn -- Subtopic C: Dimensionality Reduction Techniques…”